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Found 2 papers, 1 papers with code
DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks
In this paper, we develop a theoretical framework to approximate Bayesian inference for DNNs by imposing a Bernoulli distribution on the model weights.
Lung Cancer Screening Using Adaptive Memory-Augmented Recurrent Networks
In this paper, we investigate the effectiveness of deep learning techniques for lung nodule classification in computed tomography scans.
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